Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2024Generalized SmartScan: An Intelligent LPBF Scan Sequence Optimization Approach for 3D Part Geometriescitations
  • 2015Collective Modes and Structural Modulation in Ni-Mn-Ga(Co) Martensite Thin Films Probed by Femtosecond Spectroscopy and Scanning Tunneling Microscopy16citations
  • 2012Imaging of a patterned and buried molecular layer by coherent acoustic phonon spectroscopy ; Abbildung einer strukturierten verdeckten Moleküllage durch kohärente akustische Phononen-Spektoskopie14citations

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Chart of shared publication
Bugdayci, Bircan
1 / 1 shared
Wood, Nathaniel
1 / 1 shared
Okwudire, Chinedum
1 / 1 shared
Schäfer, Hanjo
1 / 4 shared
Grossmann, Martin
1 / 1 shared
Gusev, Vitaly
1 / 2 shared
Hettich, Mike
2 / 5 shared
Merklein, Moritz
1 / 1 shared
Schubert, Martin
2 / 11 shared
Fonin, Mikhail
1 / 17 shared
Laptev, Aleksej
1 / 4 shared
Demsar, Jure
1 / 9 shared
Luo, Yuan
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Rummel, C.
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Ristow, Oliver
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Dekorsy, Thomas
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Samwer, Konrad
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Mayer, Jan
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Jacob, Karl
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Bruchhausen, Axel
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Gusev, Vitalyi
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2015
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Co-Authors (by relevance)

  • Bugdayci, Bircan
  • Wood, Nathaniel
  • Okwudire, Chinedum
  • Schäfer, Hanjo
  • Grossmann, Martin
  • Gusev, Vitaly
  • Hettich, Mike
  • Merklein, Moritz
  • Schubert, Martin
  • Fonin, Mikhail
  • Laptev, Aleksej
  • Demsar, Jure
  • Luo, Yuan
  • Rummel, C.
  • Ristow, Oliver
  • Dekorsy, Thomas
  • Samwer, Konrad
  • Mayer, Jan
  • Jacob, Karl
  • Bruchhausen, Axel
  • Gusev, Vitalyi
OrganizationsLocationPeople

document

Generalized SmartScan: An Intelligent LPBF Scan Sequence Optimization Approach for 3D Part Geometries

  • Bugdayci, Bircan
  • He, Chuan
  • Wood, Nathaniel
  • Okwudire, Chinedum
Abstract

<jats:p>Laser powder bed fusion (LPBF) is an additive manufacturing technique that is gaining popularity for producing metallic parts in various industries. However, parts produced by LPBF are prone to residual stress, deformation, cracks and other quality defects due to uneven temperature distribution during the LPBF process. To address this issue, in prior work, the authors have proposed SmartScan, a method for determining laser scan sequence in LPBF using an intelligent (i.e., model-based and optimization-driven) approach, rather than using heuristics, and applied it to simple 2D geometries. This paper presents a generalized SmartScan methodology that is applicable to arbitrary 3D geometries. This is achieved by: (1) expanding the thermal model and optimization approach used in SmartScan to multiple layers; (2) enabling SmartScan to process shapes with arbitrary contours and infill patterns within each layer; (3) providing the optimization in SmartScan with a balance of exploration and exploitation to make it less myopic; and (4) improving SmartScan's computational efficiency via model order reduction using singular value decomposition. Sample 3D test artifacts are simulated and printed using SmartScan in comparison with common heuristic scan sequences. Reductions of up to 92% in temperature inhomogeneity, 86% in residual stress, 24% in maximum deformation and 50% in geometric inaccuracy were observed using SmartScan, without significantly sacrificing print speed. An approach for using SmartScan for printing complex 3D parts in practice, by integrating it as a plug-in to a commercial slicing software, was also demonstrated experimentally, along with its benefits in significantly improving printed part quality.</jats:p>

Topics
  • impedance spectroscopy
  • laser emission spectroscopy
  • crack
  • selective laser melting
  • decomposition